--- title: "Resources" output: rmarkdown::html_document vignette: > %\VignetteIndexEntry{resources} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` # Resources ## Article tutorials - **Multiple Methods for Visualizing Human Language: A Tutorial for Social and Behavioural Scientists** [OSF preprint](https://osf.io/preprints/psyarxiv/nxfvr_v1) - **The *text* package tutorial** [Full text on PsycNET](https://doi.org/10.1037/met0000542). [OSF preprint](https://osf.io/preprints/psyarxiv/293kt_v1). [Tutorial code](https://r-text.org/articles/psychological_methods.html) - **The Language-Based Assessment Model (L-BAM) Library** [OSF preprint](https://osf.io/preprints/psyarxiv/n8rza_v1) [Tutorial code](https://r-text.org/articles/lbam_tutorial.html) ## Selected published articles advancing the *text* package - Nilsson, A. H., Runge, J. M., Ganesan, A. V., Lövenstierne, C. V. N., Soni, N., & Kjell, O. N. (2025). *Automatic implicit motive codings are at least as accurate as humans’ and 99% faster.* *Journal of Personality and Social Psychology.* [Article link](https://doi.org/10.1037/pspp0000544) - Gu, Z., Kjell, K., Schwartz, H. A., & Kjell, O. (2025). *Natural language response formats for assessing depression and worry with large language models: A sequential evaluation with model pre-registration.* *Assessment, 10731911251364022.* [Article link](https://journals.sagepub.com/doi/full/10.1177/10731911251364022) - Nilsson, A. H., Eichstaedt, J. C., Lomas, T., Schwartz, A., & Kjell, O. (2024). *The Cantril Ladder elicits thoughts about power and wealth.* *Scientific Reports, 14(1), 2642.* [Article link](https://www.nature.com/articles/s41598-024-52939-y) ## Blog posts and tutorials - [**Implicit Motives Tutorial**](https://r-text.org/articles/implicit_motives_tutorial.html) - [**Installing and Managing Python Environments with `reticulate`**](https://r-text.org/articles/reticulate.html) - [**Creating a Singularity Container to Run HuggingFace Transformers Models in R**](https://r-text.org/articles/singularity_transformers_container.html) - [**How to Best Manage Computationally Heavy Analyses**](https://r-text.org/articles/) - [**HuggingFace Language Models Are Downloaded in `.cache`**](https://r-text.org/articles/removing_huggingface_transformers_cache_files.html) - [**HuggingFace Transformers in R: Word Embeddings Defaults and Specifications**](https://r-text.org/articles/text.html) - [**Pre-registration and Researcher Degrees of Freedom**](https://r-text.org/articles/pre_registration_and_transformers.html)